Assessing the performances of a novel decentralised scheduling approach in Industry 4.0 and cloud manufacturing contexts. Issue 20 (18th October 2021)

• Record Type: Journal Article
• Authors: Grassi, Andrea; Guizzi, Guido; Santillo, Liberatina Carmela; Vespoli, Silvestro
• Is Part Of: International journal of production research. Volume 59:Issue 20(2021)
• Page Start: 6034
• Page End: 6053
• Publication Date: 2021-10-18
• Subjects: Industry 4.0 -- cyber-physical system -- cloud manufacturing -- decentralised production planning and control -- decentralised scheduling architecture; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2020.1799105
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : The increasing globalisation process has led to a radical change in the production concept, moving from a mass production paradigm towards one of mass customisation (MC), and focusing on value creation by pursuing customers' needs and increasing responsiveness. The rapid development of information technologies has also made it possible to create new manufacturing paradigms, such as Industry 4.0 and cloud manufacturing, in which the increased level of autonomy is one of the key concepts for tackling new market challenges. This paper proposes a decentralised scheduling approach that improves the performance of production systems while minimising the usually high work-in-progress (WIP) requirements of the classic centralised scheduling and inventory production control system. Using a semi-heterarchical Manufacturing Planning and Control (MPC) architecture and integrating the Industry 4.0 innovation in a cloud manufacturing environment, this work contributes to the design of the lower level of the MPC architecture. The resulting production controller can allocate jobs following different dispatching rules dynamically. The performances of the proposed approach were assessed for different production scenarios and control parameter settings through an exhaustive experimental campaign based on hybrid simulation tools. The results showed that the proposed low-level controller led to a productivity increase while delivering increased responsiveness.